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ICML
2007
IEEE
14 years 8 months ago
Learning to combine distances for complex representations
The k-Nearest Neighbors algorithm can be easily adapted to classify complex objects (e.g. sets, graphs) as long as a proper dissimilarity function is given over an input space. Bo...
Adam Woznica, Alexandros Kalousis, Melanie Hilario
DICTA
2003
13 years 9 months ago
Learning Semantic Concepts from Visual Data Using Neural Networks
For content-based image retrieval techniques, query image is used to pick up and rank some relevant images from a database using some certain similarity metric. If semantic feature...
Xiaohang Ma, Dianhui Wang
EENERGY
2010
13 years 11 months ago
Towards energy-aware scheduling in data centers using machine learning
As energy-related costs have become a major economical factor for IT infrastructures and data-centers, companies and the research community are being challenged to find better an...
Josep Lluis Berral, Iñigo Goiri, Ramon Nou,...
IJCNN
2000
IEEE
14 years 18 hour ago
Metrics that Learn Relevance
We introduce an algorithm for learning a local metric to a continuous input space that measures distances in terms of relevance to the processing task. The relevance is defined a...
Samuel Kaski, Janne Sinkkonen
ICMLA
2009
13 years 5 months ago
Mahalanobis Distance Based Non-negative Sparse Representation for Face Recognition
Sparse representation for machine learning has been exploited in past years. Several sparse representation based classification algorithms have been developed for some application...
Yangfeng Ji, Tong Lin, Hongbin Zha